The Temporal Morphology of Infrasound Propagation · The Temporal Morphology of Infrasound...

The Temporal Morphology of Infrasound Propagation

DOUGLAS P. DROB,1 MILTON GARCES,2 MICHAEL HEDLIN,3 and NICOLAS BRACHET4

Abstract—Expert knowledge suggests that the performance of

automated infrasound event association and source location algo-

rithms could be greatly improved by the ability to continually

update station travel-time curves to properly account for the hourly,

daily, and seasonal changes of the atmospheric state. With the goal

of reducing false alarm rates and improving network detection

capability we endeavor to develop, validate, and integrate this

capability into infrasound processing operations at the International

Data Centre of the Comprehensive Nuclear Test-Ban Treaty

Organization. Numerous studies have demonstrated that incorpo-

ration of hybrid ground-to-space (G2S) enviromental specifications

in numerical calculations of infrasound signal travel time and

azimuth deviation yields significantly improved results over that of

climatological atmospheric specifications, specifically for tropo-

spheric and stratospheric modes. A robust infrastructure currently

exists to generate hybrid G2S vector spherical harmonic coeffi-

cients, based on existing operational and emperical models on a

real-time basis (every 3- to 6-hours) (DROB et al., 2003). Thus the

next requirement in this endeavor is to refine numerical procedures

to calculate infrasound propagation characteristics for robust

automatic infrasound arrival identification and network detection,

location, and characterization algorithms. We present results from a

new code that integrates the local (range-independent) sp ray

equations to provide travel time, range, turning point, and azimuth

deviation for any location on the globe given a G2S vector

spherical harmonic coefficient set. The code employs an accurate

numerical technique capable of handling square-root singularities.

We investigate the seasonal variability of propagation character-

istics over a five-year time series for two different stations within

the International Monitoring System with the aim of understanding

the capabilities of current working knowledge of the atmosphere

and infrasound propagation models. The statistical behaviors or

occurrence frequency of various propagation configurations are

discussed. Representative examples of some of these propagation

configuration states are also shown.

Key words: Infrasound, atmospheric variability, climatology,

automated event detection, source location, CTBTO, IDC, IMS.

1. Background

The purpose of the automated infrasound pro-

cessing developed at the IDC is to detect coherent

signals measured on individual IMS sensors (CHRISTIE

et al., 2001), highlight the most significant detections

as ‘‘phases’’ (as opposed to ‘‘noise’’), and subse-

quently group these phases to form and locate

hypocenters, so-called ‘‘events’’. The phases are

determined using the progressive multi-channel cor-

relation (PMCC) method (CANSI, 1995) which

distinguishes the coherent signals produced by natu-

ral and man-made sources from incoherent ambient

background noise which may also be of natural,

cultural, or instrumental origin. A wide variety of

sources are regularly recorded worldwide by the IMS

network; ocean activity, mountain associated waves,

volcanic eruptions, earthquakes, thunderstorms,

meteors, avalanches, auroras, rocket launches and re-

entries, aircraft, mine-blasts, accidental explosions,

and industrial noise. It is important for the IDC to

detect, locate, and categorize these sources to contrast

with nuclear explosions; the task of the organization.

The detection, location, and characterization

algorithms (henceforth DLC) described by BROWN

et al., (2002a) may be used to locate the terminal

burst point of exploding meteors, the origin time of

volcanic eruptions, and the location of avalanches

and rock slides, as well other null sources relevant to

CTBTO operations (LE PICHON et al., 2008b; HEDLIN

et al., 2002). Although the various natural events

represent false alarms for the CTBTO, they also

provide valuable ground-truth information that can be

1 Space Science Division, Naval Research Laboratory,

Washington, DC, USA. E-mail: [email protected] Infrasound Laboratory, University of Hawaii, Manoa, USA.

E-mail: [email protected] Laboratory for Atmospheric Acoustics, University of

California, San Diego, USA.4 International Data Centre, Provisional Technical

Secretariat, CTBTO, Vienna, Austria.

Pure Appl. Geophys. 167 (2010), 437–453

� 2010 US Government

DOI 10.1007/s00024-010-0080-6 Pure and Applied Geophysics

used to constantly fine-tune and check the integrity of

the system, insuring verifiability of the treaty. For

example, terminal bursts of meteors with an average

yield of one kiloton occur in the earth’s atmosphere

several times per year (NEMTCHINOV et al., 1997;

BROWN et al., 2002b).

To facilitate rapid computation, today’s automated

DLC algorithms rely upon precompiled station travel-

time information (BROWN et al., 2002a). The precom-

piled information, which is typically average

propagation velocity and azimuth deviation, describes

how an observed signal was affected by the back-

ground environment on its way from source to receiver.

The application of this knowledge provides improved

source location and signal association estimates.

Our objective is to reduce IDC false alarm rates

and improve detection capability by reducing the

sources of uncertainty in the existing model physics

and DLC methodologies. Analyses of ground-truth

events have shown that observationally constrained

atmospheric specifications are superior to average

climatology (LE PICHON et al., 2002, 2005; HERRIN

et al., 2006). This is particularly true for tropospheric

and stratospheric propagation for which there are

several global operational numerical weather predic-

tion systems such as the NOAA Global Forecast

System (KALNAY et al., 1990) and ECMWF (COURTIER

et al., 1998; BECHTOLD et al., 2008). Unfortunately,

these systems are currently limited in their altitude

extent due to the unavailability of routine operational

satellite observations above approximately 80 km.

The ground-to-space (G2S) environmental specifica-

tion system was therefore developed to provide a

compact numerical weather prediction post-processor

and infrasound propagation calculation preprocessor

(DROB et al., 2003) to account for all altitudes perti-

nent to infrasound propagation. The system serves as

a placeholder until operational numerical weather

prediction models and data sets include the lower

thermosphere.

In addition to requiring up-to-date knowledge

about the atmospheric state for improving DLC

algorithms, an acoustic wave propagation model is

required to compute how observed infrasound signals

relate back to their source. In discrete inverse theory

(MENKE, 1989) this is known as a forward model.

There are a number of propagation modeling

techniques available such as ray tracing (GOSSARD and

HOOKE, 1975), parabolic equations (LINGEVITCH et al.,

2002), and normal modes (PIERCE, 1967). Unfortu-

nately with detailed physics comes greater

complexity. The approach must not be so primitive

that any value added from near-real-time atmospheric

specification has no meaningful influence; in turn, the

technique must not be so complicated that imple-

mentation is impractical in automated DLC

algorithms. The data and procedures must be readily

available and simple enough to integrate into opera-

tional monitoring systems.

2. The sp Equations

At present the sp equations of GARCES et al.,

(1998) provide a good balance of simplicity and

geophysical information content for automated DLC

algorithms, particularly in conjunction with near-real-

time atmospheric specifications. In general, the

acoustic ray-tracing approach represents the propa-

gation or translation and rotation of an acoustic

wavefront through space and time. The sp equations

are an expression of the Eikonal ray-tracing equations

(LIGHTHILL, 1978; GOSSARD and HOOKE, 1975) in

integral form with the approximations of range

independence and no vertical wind. For this, each ray

or wavefront element can be uniquely represented by

an invariant ray parameter (p),

p ¼ kz

co1þ kzuo

co

� ��1

; ð1Þ

which depends on the static sound speed at the

receiver (co), the vertical wave number kz = sin(q)

where q is elevation angle, and uo the horizontal wind

velocity along the direction of propagation at the

receiver. This ray parameter is also the reciprocal of

the intrinsic horizontal phase velocity of the wave

Vh = 1/p, therefore;

Vh ¼co

kz1� kz

co

� �: ð2Þ

The equation for the along track range travelled

between bounces, i.e., propagation from the bottom

of the atmospheric duct to the top and back down

again in a phase loop is

438 Douglas P. Drob et al. Pure Appl. Geophys.

R z; pð Þ ¼ 2

Zz pð Þ

zo

w z; pð Þ p

1� uðzÞpð Þ þ u zð Þf zð Þ� �

dz;

ð3Þ

where zo is the lower limit of integration (typically

zero or the surface altitude) and z(p) is the upper

limit, which is the first root above zo of the charac-

teristic function.

w z; pð Þ ¼ f zð Þ � p2

1� uðzÞpð Þ2

" #�1=2

: ð4Þ

This root represents the turning point of the ray

following from classical WKB ray theory which

states that a ray will turn when its horizontal phase

velocity (Vh) matches that of the background effec-

tive sound speed, c(z) ? u(z) where these are the

adiabatic sound velocity and horizontal wind speed

along the direction of propagation, respectively. The

infrasound propagation characteristics in Eqs. 3 and 4

are a function of the local vertical profiles of

f(z) = 1/c2(z) and u(z) as well. The corresponding

travel time (T) for a phase loop is similarly

T z; pð Þ ¼ 2

Zz pð Þ

zo

w z; pð Þf zð Þdz: ð5Þ

The celerity (V), or average group velocity from

the source to the receiver is simply V = R/T. Lastly,

the apparent azimuth deviation is computed as

X = arctan-1(Q/R) where the transverse offset (Q)

for a phase loop is

Q z; pð Þ ¼Zz pð Þ

zo

w z; pð Þf zð Þv zð Þdz; ð6Þ

where v(z) is the horizontal wind component trans-

verse to the direction of propagation. Throughout this

paper, all of the results are computed in the frame of

reference of the receiver as opposed to the source by

simply reversing the sign of the wind fields. It can be

shown that this is also equivalent to integrating the

Eikonal ray equations in differential form with a

negative time step.

A discussion of the methodology for the estima-

tion of the eigenrays associating a received signal

with a given source is beyond the scope of the present

work. Relevant, however, is the fact that for a specific

eigenray the measured azimuth deviation is an

apparent effect similar to that of an airplane yawing

in a crosswind in order to maintain a constant bear-

ing. The acoustic wavefront must be skewed at some

angle X with respect to the great circle path in order

to offset the net lateral advection from transverse

wind components; in other words so that the net

transverse offset at the top and bottom of the phase

loop are zero. Although the total path does not

deviate from the true great circle path between source

and receiver, in the presence of transverse winds the

wavefront can depart from the great circle path any-

where else in the phase loop. Over one range of

altitudes a crosswind may push the ray off the great

circle path, while at other altitudes a crosswind in the

opposite direction may push the ray back onto the

great circle path. Furthermore, the ray may deviate to

one side of the path on the up leg and the other side of

the path on the down leg. This is also an important

factor that needs to be considered when signals are

observed from a source at altitude such as a bolide.

Care must be taken in automated and interactive DLC

algorithms when applying calculated values of X to

correct the array observations for apparent azimuth

deviation. If topography and atmospheric range

variations are included then the actual path can be

even more complicated, however the overall charac-

teristics remain the same.

The crux of solving the sp integrals accurately is

the treatment of the inverse square-root singularity in

the function w(z) at the upper limit of the domain. At

any point in the domain (i.e. for any given p) the root

is calculated by first bracketing it with a grid search

and then applying Brent’s method to approximate the

root to a high degree of accuracy (PRESS, 1989).

Knowing the location of the square-root singularity

z(p), Eqs. (3)–(6) can then be integrated with a

Romberg method employing a modified midpoint

rule that can handle inverse square-root singularities

at the upper bound (PRESS, 1989). For all of the

numerical results presented, continuous functional

values for u(z), w(z), c(z), and f(z) are calculated by

cubic spline interpolation of gridded G2S values with

Dz = 125 m. Note that the calculation of vertical

derivatives is not required to integrate Eqs. (3)–(6).

Vol. 167, (2010) Temporal Morphology of Infrasound Propagation 439

These integrals may also be evaluated for sources at

altitude such as bolides by including a second term

for the fractional part of the propagation phase loop

where the limits of integration have been adjusted

accordingly.

Two factors are relevant to current IDC DLC

processing with respect to signals generated by

sources well above the ground where the expected

number of detectable phases can double at distant

recording stations owing to the fact that a source will

have both upward and downward directed acoustic

components. First, current automated procedures

focus on picking the onset time of the fastest infra-

sound arrival, and when and where closely spaced

multiple arrivals exist, they tend to be averaged into a

single characteristic by the parameters of the auto-

mated PMCC feature extraction algorithms.

Secondly, progress has been made to demonstrate

that it is possible to estimate hypocenter altitude at

the level of interactive IDC analyst expert review,

where manual identification of tropospheric, strato-

spheric, and thermospheric phases is possible; and in

particular in conjunction with additional information

from detections by the seismic, and auxiliary seismic

components of the IMS network (EDWARDS and

HILDEBRAND, 2004; ARROWSMITH et al., 2007; LE

PICHON et al., 2008a). As experience progresses, it

will eventually be possible to implement these con-

siderations into automated IDC processing, however

as is the case in seismology, hypocenters depths are

difficult to compute without a dense local network or

specific depth phases. Automated hypocenter height

estimates via infrasound will thus likely only be

approximate until an IDC analyst can refine them.

Example climatological profiles from the

HWM93/MSISE-00 empirical models (HEDIN et al.,

1996; PICONE et al., 2002) for January 1, 2005 at

00:00 UT for a typical northern hemisphere mid-lat-

itude station (I56US) are shown in Fig. 1. Illustrative

sp calculations corresponding to these example pro-

files are shown in Fig. 2. These calculations are

performed over all observable azimuths for elevation

angles from 0� to 35�. The horizontal phase velocity

(Vh) of the parameter space over the domain is shown

in panel A. Recall that this is only a function of the

atmospheric conditions at the detector. Panel B shows

a contour plot of the effective sound velocity as a

function of altitude (z) and backazimuth. The win-

tertime stratospheric wind jet near 55 km can be

observed, with winds toward the detector at -90�,

and away from the detector at ?90�. The turning

points of all incoming rays at elevation angles of 5�,

10�, and 15� are also indicated. The corresponding

turning heights of the rays, over the entire domain, is

shown in panel C. Two predominant ducts are present

at this time and location, the thermospheric duct for

all backazimuths and the eastward stratospheric duct

from the wintertime stratospheric zonal wind jet. The

260 280 300 320 340 360 380 4000

20

40

60

80

100

120

Adiabatic Sound Velocity

Velocity (m/s)

Alti

tude

(km

)

−60 −40 −20 0 20 40 60

Wind Velocity

Velocity (m/s)

Zonal

Meridional

Figure 1Climatological profiles; adiabatic sound velocity (left), zonal wind (right solid), and meridional wind (right, dashed) from the HWM93/

MSISE-00 empirical models (HEDIN et al., 1996; PICONE et al., 2002) for January 1, 2005 at 00:00 UT


Phase Velocity (m/s)

Backazimuth (from receiver)

Ele

vatio

n

−150 −100 −50 0 50 100 1500

5

10

15

20

25

30

330

340

350

360

370

380

390

400

Effective Sound Velocity (m/s)

Backazimuth (Deg)

Alti

tude

(km

)

−150 −100 −50 0 50 100 1500

20

40

60

80

100

120

250

300

350

400

Turning Height (km)

Backazimuth

Ele

vatio

n

−150 −100 −50 0 50 100 1500

5

10

15

20

25

30

0

20

40

60

80

100

120Celerity (m/s)

Backazimuth

Ele

vatio

n

−150 −100 −50 0 50 100 1500

5

10

15

20

25

30

200

220

240

260

280

300

320

340

360

Range (km)

Backazimuth

Ele

vatio

n

−150 −100 −50 0 50 100 1500

5

10

15

20

25

30

0

50

100

150

200

250

300

350

400

450

500Azimuth Deviation (Deg)

Backazimuth

Ele

vatio

n

−150 −100 −50 0 50 100 1500

5

10

15

20

25

30

−10

−8

−6

−4

−2

0

2

4

6

8

10

A B

C D

E F

Figure 2sp ducting characteristics for I56US (48.2640�N, 117.1257�W) on January 1, 2006 0:00 UTC as function of backazimuth at the detector. Panel

A show the horizontal phase velocity for all elevations from 0� to 35�, Panel B shows the effective sound speed velocity in the direction of

propagation, Panel C the ray turning height, panel D the celerity, and E the range to first bounce, and F the apparent azimuth deviation. The

contour lines in panel B indicate the turning height of rays launched at elevation angles of 5�, 10�, and 15�, respectively


dark blue area represents a region where the acoustic

energy is immediately refracted downward toward

the earth’s surface by the ambient atmospheric con-

ditions. Panels D, E, and F show the celerity (V),

range (R), and apparent azimuth deviation (X) over

the computational domain, respectively. A very sta-

ble and accurate result can be obtained over the entire

domain, including in the vicinity of the cusp regions

where fast propagation modes exist (EVERS and HAAK,

2007). These fast modes can be seen near the tran-

sition from the stratospheric to the thermospheric

ducts for look directions to the west.

Several limitations resulting from the various

approximations in the sp method such as the short-

comings of linear ray-tracing theory (MILLET et al.,

2007), the lack of explicit range dependence (DROB

et al., 2003), and the influence of internal scattering

by internal gravity waves (CHUNCHUZOV, 2004;

OSTASHEV et al., 2005) are noteworthy but beyond the

scope of the present discussion. With the doubling of

processing capacities every few years following

Moore’s Law, more complex calculations that

account for range-dependent variations in the back-

ground atmosphere should be investigated and

eventually implemented in automated DLC algo-

rithms. The objective at hand is to provide

geophysical insight to demonstrate that the utilization

of climatological travel times in DLC algorithms is at

best outdated in comparison to the possibility of

calculating them in real time following from recent

progress in atmospheric specification and infrasound

propagation codes.

3. Results

Classic pioneering work by GEORGES and BEASLEY,

(1977) and others, which relied on limited knowledge

of the atmosphere, developed an appreciation for how

infrasound ducting characteristics vary with latitude

over the year. With more recent information from

thirty-five years of satellite and ground-based atmo-

spheric wind and temperature measurements, DROB

et al., (2003) investigated how infrasound propaga-

tion characteristics varied over the globe at a given

universal time; in particular, how acoustic energy is

partitioned between the troposphere, stratospheric,

and thermosphere ducts. To provide some context,

Fig. 3 shows the global distribution of infrasound

ducting characteristics for an arbitrary time of 05/24/

2006 00:00 UT. For a particular altitude level, each

global map represents the fraction of acoustic energy

from an isotropically radiating acoustic point source

on the ground, summed over all possible propagation

directions (see DROB et al., 2003).

The regions where tropospheric ducting occurs are

shown in the top panel. Ducting along the tropo-

spheric jet stream can also be seen in the Southern

Hemisphere. Marine inversion layers also occurred

off the west coast of California and Africa, as well as

near the Korean Peninsula. Stratospheric ducting

(middle panel) is seen in the Northern And Southern

Hemisphere mid-latitude regions but is absent in the

equatorial regions. The lower panel shows the

remaining thermospheric ducting fractions. Interest-

ing correlations in the thermospheric ducting fractions

with continental landmasses and lower atmospheric

ducting fractions can also be seen. The inverse cor-

relations between the upper and lower atmospheric

ducting fractions are due to the fact that what was not

ducted in the lower atmosphere can be ducted in the

upper mesosphere and lower thermosphere.

Following the work of DROB et al., (2003), we

now present several case studies based on the cal-

culation of a multiyear time series of infrasound

propagation characteristics for two of the IMS in-

frasound stations; I56US a mid-latitude Northern

Hemisphere station at (48.26�N, 117.13�W), and

I55US a polar latitude Southern Hemisphere station

at (77.74�S, 167.58�E). We compare and contrast the

results calculated from both climatology (HWM93/

MSISE-00) and hybrid G2S specifications. For these

two IMS stations, we present a five-year long-time

series from September 13, 2002 to April 30, 2007 at

6 h intervals (49 daily) of the infrasound ducting

characteristics of ray turning heights z(p), celerity (V)

and backazimuth (X). The later two have direct

application in infrasound DLC algorithms.

In the detection algorithms described by BROWN

et al., (2002a) currently in use at the IDC, backazi-

muths receive a slightly greater statistical emphasis

(1.0) as compared to travel times (0.8) in the calcu-

lation of a metric (R) for the trigging of an automatic

event (R[ 3.55) and Reviewed Event Bulletin


Troposphere

0.00 0.05 0.10 0.16 0.21

Stratosphere

0.00 0.10 0.20 0.31 0.41

Thermosphere

0.40 0.49 0.58 0.67 0.76

Figure 3Tropospheric, stratospheric, and thermospheric infrasound ducting fractions for 05/24/2006 00:00 UT


(REB) (R[ 4.6). This detection criteria effectively

defines a significant event as one that can be estab-

lished by at least two well-defined and intersecting

back azimuths for which the associated travel times

do not also violate causality (BROWN et al., 2002a).

More recently, a novel detection scheme was devel-

oped by ARROWSMITH et al., (2008) that dynamically

adjusts network detection thresholds in real time to

account for the presence of correlated and varying

background noise. Furthermore, ARROWSMITH et al.,

(2008) demonstrated that the new algorithm has

excellent performance characteristics in the presence

of clutter, suggesting the approach provides a viable

means to reduce the number of false alarms that need

to be reviewed by a human analysis. Neither

approach currently accounts for the hourly, daily, or

seasonal changes of the travel time or azimuth devi-

ation resulting from the corresponding changes in the

atmospheric conditions; the inclusion of which would

further allow for a more accurate calculation of the Rmetric thus improving the network sensitivity and

reducing the number of false alarms.

4. I56US

Figure 4 shows the computed turning points of

infrasound for arrivals at I56US for an elevation of

5�. The top panel shows the results calculated from

the climatology and the lower panel the results cal-

culated with the hybrid G2S specification. The

alternating seasonal pattern, where eastward strato-

spheric propagation is observed in the wintertime and

westward stratospheric propagation is observed in the

summer time, is evident. Ducting caused by the tro-

pospheric jet stream for predominantly eastward

propagating arrivals, as well as occasionally for

northward and southward directions, can also be seen.

Furthermore, occasional stratospheric ducting in both

the westward and eastward directions, related to

global-scale dynamical instabilities in the strato-

sphere, can sometimes occur during the winter

months. As would be expected but not shown here,

the corresponding results for lower elevation angles

exhibit more tropospheric and stratospheric ducting

for lower incoming elevations and less for large

elevation angles (more thermospheric ducting).

Figure 5a shows the azimuth deviation for west-

ward arrivals from the five-year time series at I56US;

climatological values are indicated in red and results

from the hybrid specifications in blue. There is an

average scatter in the hybrid specifications of about

±2�, on par with the climatological predictions, plus

occasional excursions of up to ±4� during the winter

months. The four interleaved bands in the climato-

logically predicted variations result from the different

local times under the influence of the solar migrating

tides as described by GARCES et al., (1998). Figure 5b

shows the azimuth deviation for southward arrivals

with excursions up to 10� in January 2003, and on

average up to 7.5� during wintertime. In addition, there

is an asymmetry with respect to the summer months

with deviations of up to -3�, which tend to be more

stable. These wide ranging azimuth deviations result

from the annual variations of the stratospheric wind jet

which is predominantly eastward, lower, stronger, and

variable in the wintertime, as compared to the sum-

mertime jet which is westward, higher, and stable.

Figure 6a shows a time series of celerity for

I56US for eastward arrivals again at 5� elevation,

calculated with hybrid G2S and empirical atmo-

spheric specifications. A band of arrivals at 340 m/s,

which are comprised of both lower tropospheric,

upper tropospheric, and even stratospheric modes, is

evident. Random departures of up to 30 m/s from

climatological estimates and seasonal variations

occur during wintertime for the other branch of

arrivals between 250 and 320 m/s.

Figure 6b presents the comparison of celerity for

all southward arrivals at 5� elevation. Note the

occasional tropospheric modes (330 m/s) with a half-

width of 20 m/s, including seasonal oscillations. The

predicted tidal oscillations are also more significant.

With respect to the climatology, lower atmospheric

ducting to the north and south are generally not

expected as the meridional wind fields average to

zero over the globe.

Figure 6c shows the results for westward arrivals.

Of note is the presence of occasional tropospheric

arrivals (340 m/s) with clear seasonal variability. If

not properly accounted for (i.e. given the appropriate

statistical weighting) these could result in spurious

associations and poor source localizations. The results

also show that there is pronounced annual variability


with stable stratospheric modes in the summer time,

transitioning to thermospheric modes in the winter-

time as was shown in Fig. 4. The existence of sporadic

stratospheric modes occurring in both the eastward

and westward directions in late winter are associated

with the dynamical instability of the stratospheric

wind jet driven by vertically propagating planetary

waves. Disturbances associated with sudden strato-

spheric warmings (MANNEY et al., 2008) can even

result in prolonged intervals of westward winds in the

stratosphere during the wintertime.

5. I55US

The second set of illustrative examples is for the

polar Southern Hemisphere station I55US. The

comparison of turning points calculated with clima-

tology and the hybrid specifications for rays that will

enter the detector at 5� elevation, as a function of

backazimuth and time, are shown in Fig. 7. While the

overall morphology of the climatological and hybrid

specifications for the mid-latitude I56US station is

generally similar in Fig. 4, this is not the case for

Backazimuth

Dat

e

−150 −100 −50 0 50 100 150

Oct02Jan03Apr03Jul03




Oct06Jan07Apr07

0

20

40

60

80

100

120

Backazimuth

Dat

e

−150 −100 −50 0 50 100 150





Oct06Jan07Apr07

0

20

40

60

80

100

120

I56US, Turning Height (km), 5 degree elevation


Figure 4The turning height for all rays at I56US that enter the receiver at an elevation angle of 5�. The upper panel shows the results calculated from

the HWM/MSIS climatology and the lower panel the results from the hybrid G2S atmospheric specifications


I55US. Again, the day-to-day variability, whether for

a tropospheric, stratospheric, or thermospheric duct,

is more pronounced in the real atmosphere (G2S

hybrid) than the calculations with the monthly aver-

age climatology would imply. From these examples it

should be obvious that climatology does not accu-

rately predict the occurrence of tropospheric and even

stratospheric ducting in the region.

The time series of computed celerity for westward

arrivals is shown in Fig. 8a. Annual variations of

hybrid G2S characteristics follow the climatology of

the predominate stratospheric and thermospheric

modes reasonably well, but not perfectly. Like for the

Northern Hemisphere mid-latitudes, greater variabil-

ity exists in the computed propagation characteristics

during wintertime. A predominant but transient lower

atmospheric mode, disappearing in summer, with an

−5

−4

−3

−2

−1

0

1

2

3

4

5

Deg

rees

Jan03 Jul03 Jan04 Jul04 Jan05 Jul05 Jan06 Jul06 Jan07−5

0

5

10

15

Date

Westward

Southward

Azimuth Deviation, I56US

Deg

rees

Figure 5Time series of azimuth deviation of westward (top) and southward (bottom) arrival for I56US at an elevation angle of 5�. Predictions using

climatology are in red. Predictions using the hybrid (G2S) model are in blue

Figure 6Time series of the celerity for 5� elevation arrivals at I56US for

eastward, southward, and westward directions, respectively. The

color coding is as described in the caption for Fig. 5

c


220

240

260

280

300

320

340

360

Cel

ocity

(m

/s)

Southward

220

240

260

280

300

320

340

360

Cel

ocity

(m

/s)

Eastward

Jan03 Jul03 Jan04 Jul04 Jan05 Jul05 Jan06 Jul06 Jan07220

240

260

280

300

320

340

360

Date

Cel

ocity

(m

/s)

Westward

Celerity, I56US


average celerity of about 310 m/s is also present. The

340 m/s celerities observed at I56US (Fig. 6) are

generally not be observed at I55US as the polar tro-

posphere is colder and the station is too far poleward

to be influenced by the tropospheric jet stream.

Figure 8b shows the results for southward arrivals,

which vary from 260 to 325 m/s, again exhibiting

significant departures from climatological predictions.

Lastly, we consider the azimuth deviations for

IMS station I55US. The time series of southward

arrivals is shown in Fig. 9a, for which there are

asymmetric seasonal variations with occasional spo-

radic excursions of over 10�, and up to 7.5� on

average. Significant local-time (tidal) variations of the

thermospheric modes are again present in the clima-

tology. The results shown in Fig. 9b for the westward

Backazimuth

Dat

e

−150 −100 −50 0 50 100 150





Oct06Jan07Apr07

0

20

40

60

80

100

120

Backazimuth

Dat

e

−150 −100 −50 0 50 100 150





Oct06Jan07Apr07

0

20

40

60

80

100

120



Figure 7The turning height for all rays at I55US that enter the receiver at an elevation angle of 5�. The upper panel shows the results calculated from

the HWM/MSIS climatology and the lower panel the results from the hybrid G2S atmospheric specifications


arrivals at I55US depart widely from the average

climatology going from ?4� to -4� over a month.

6. Discussion/Conclusion

As described in BROWN et al., (2002a) one could

imagine tables of statistical propagation characteris-

tics comprised of several dominant modes that could

be implemented in operational DLC algorithms; a

constant phase at 310–340 m/s and an annual varying

one with stratospheric and thermospheric phases. In

future IDC software updates, these could and should

also be a function of day of the year, look direction,

and station. Histogram analysis could be used to

establish preferred propagation modes with uncer-

tainties and assigned probabilities based on half-

widths; however, direct utilization of the procedures

we have outlined here on a daily basis is just as easy

to implement. At present the IDC uses travel-time

tables which are independent of season, though do

depend on the elevation of arrival.

220

240

260

280

300

320

340

Cel

erity

(m

/s)

Jan03 Jul03 Jan04 Jul04 Jan05 Jul05 Jan06 Jul06 Jan07240

250

260

270

280

290

300

310

320

330

340

Date

Cel

erity

(m

/s)

Westward

Southward

Celerity, I55US

Figure 8Time series of the celerity for 5� elevation arrivals at I55US for westward and southward, respectively. The color coding is as described in the

caption for Fig. 5


Furthermore, from the consideration of the vari-

ability of backazimuth and celerity presented, it is

clear that the current seasonal averaged travel-time

tables provide a poor representation of the day-to-day

and month-to-month variations, and thus limit the full

potential of the CTBTO automated infrasound DLC

algorithms. The inherent variability is simply lost in

the histogram analysis. It should be noted that in

concert with the other monitoring technologies of the

CTBTO, the current infrasound algorithms are pass-

able, but improvable, as has been demonstrated by

numerous researchers and results. Additional work,

following examples such as ARROWSMITH et al.,

(2008); LE PICHON et al., (2008c) should be under-

taken in order to ascertain the value added to the

system in terms of false alarm rates and network

detection thresholds with careful consideration of the

computational complexity and burden introduced into

the existing operational system.

With respect to caveats for the calculations pre-

sented here, for certain locations and times the

dynamical variability of the upper mesospheric and

−5

0

5

10

15

Deg

rees

Jan03 Jul03 Jan04 Jul04 Jan05 Jul05 Jan06 Jul06 Jan07−5

−4

−3

−2

−1

0

1

2

3

4

5

Date

Deg

rees

Southward

Westward

Azimuth Deviation, I55US

Figure 9Time series of southward and westward arrivals for I55US at an elevation angle of 5�, respectively. The color coding is as described in the

caption for Fig. 5


lower thermospheric modes may be even greater in

reality than calculated here after accounting for

observed and documented non-migrating tides

(FORBES et al., 2003), day-to-day and inter-seasonal

tidal variability (FRITTS and ISLER, 1994; LIEBERMAN

et al., 2007), and the existence of vertically propa-

gating and stationary mesosphere lower thermosphere

planetary waves (SMITH, 1996; MCLANDRESS et al.,

2006) above 55 km. These effects are not yet fully

included in either the empirical climatology or hybrid

G2S atmospheric specification. The HWM93 model

is also known to underestimate the magnitude of the

migrating tides for certain seasons and latitudes.

A recent update of HWM (HWM07) by DROB et al.,

(2008) resolves most of the issues related to the

amplitude and phases of the migrating solar tides in

the mesosphere and lower thermosphere. Given a

proper statistical treatment of the present uncertain-

ties, limitations of the present atmospheric

specifications above 55 km should not invalidate the

applicability of the work described here to DLC

algorithms. In particular, tropospheric and strato-

spheric modes, which have a much greater signal to

noise ratio are more likely to be detected and not

subject to these problems.

The sp and G2S software which produced the

results presented here are specifically designed to be

utilized at the IDC in batch mode via a shell script in

order to compute the local propagation characteristics

for all IMS infrasound stations in real time. These

codes can also be invoked interactively by an IDC

analysist. For a given station and time the sp calcu-

lations only require a few seconds to complete. The

process is relatively fast compared to the periodic

calculations of the global G2S coefficient set from

available atmospheric data sources, requiring several

minutes to downloading available global weather

fields and perform the vector spherical harmonic

transforms. With the addition or allocation of a single

dedicated compute node that is accessible to the

operational DLC system, the travel-time characteris-

tics for all sixty IMS infrasound stations could be

updated every 60 min. Compared to automated DLC

calculations from climatological travel-time tables

gains in system performance could thus be achieved.

Recent ground-truth events investigated by the

infrasound research community have clearly

demonstrated that accurate atmospheric specifications

are required to properly explain observed infrasound

signals. In tandem, the atmospheric science commu-

nity is continually improving and currently producing

reliable specifications of the atmospheric state that

can be utilized to improve automated DLC algo-

rithms. Given the advances and availability of low-

cost computing resources, and the reliable openly

available real-time atmospheric specifications such as

provided by NOAA and ECMWF there are no good

reasons, technical or otherwise, why near-real-time

travel-time tables should not be used in infrasound

propagation calculations. Of course when these sys-

tems are brought online it is important to continually

monitor and evaluate the performance with the many

naturally occurring geophysical, as well as coinci-

dental man-made, ground-truth events. One

possibility as already demonstrated by similar

research is the example of the analysis of the multi-

year time series of volcanic observations at I22FR

(LE PICHON et al., 2005). Lastly for robust event

location and screening of automated event bulletins

by human analysts (BROWN et al., 2002a), we rec-

ommend that detailed propagation modeling

techniques that account for range dependence

(GOSSARD and HOOKE, 1975), topography (ARROWSMITH

et al., 2007), and other effects such as interval gravity

waves (OSTASHEV et al., 2005; CHUNCHUZOV, 2004) be

utilized.

This paper has presented time series of infrasound

propagation characteristics. A number of physical

approximations where made to keep these calcula-

tions simple and robust. Through these calculations,

we have argued that precomputed monthly average

travel-time tables are poor for operational DLC

algorithms. To this end, we have advanced progress

toward the integration of real-time infrasound prop-

agation travel-time tables into automated IMS

processing.

Acknowledgments

The methodologies and tools presented here were

developed in part in an effort supported by the Office

of Naval Research to investigate whether signals

from infrasound ground-truth events could be


inverted to obtain information about the atmosphere,

i.e., ground-to-space infrasound acoustic tomogra-

phy, such as is currently in routine use in

oceanography and seismology.

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(Received November 21, 2008, revised January 12, 2009, accepted April 21, 2009, Published online March 10, 2010)


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